Stochastic chemical kinetic models. Medical search. Frequent questions

A central challenge in computational modelling of dynamic biological systems is parameter inference from experimental time course measurements. (warwick.ac.uk)
she has taught modules involving CRN modelling and currently leads the 2nd year laboratory module at USFD, delivering computational modelling workshops to 180 undergraduates. (europa.eu)
Consequently, computational modeling, specifically multiscale modeling has emerged as a powerful tool for investigating the underlying mechanisms of thrombus growth under flow [ 2 - 15 ]. (frontiersin.org)
The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. (logesoft.com)
The study addresses two of the main challenges facing combustion modeling for transportation fuels: simultaneous simulation of non-related combustion problems and reducing the computational cost of the modeling process itself. (sjsu.edu)
Stochastic effects can be important for the behavior of processes involving small population numbers, so the study of stochastic models has become an important topic in the burgeoning field of computational systems biology. (biomedcentral.com)
However analysis techniques for stochastic models have tended to lag behind their deterministic cousins due to the heavier computational demands of the statistical approaches for fitting the models to experimental data. (biomedcentral.com)
With the growing awareness of stochasticity in biology and the increasing use of stochastic models in computational systems biology, there is a need to develop new analysis and computational techniques for studying, understanding and designing these stochastic models. (biomedcentral.com)
Parameter inference for continuous deterministic models has a considerable body of research literature and can often be converted into an optimization problem for which many computational methods are available [ 20 ]. (biomedcentral.com)
More on the computer science side, we plan to follow some directions to improve the underlying computational model and the linguistic primitives it provides as suggested by the experiments carried out, e.g. by introducing a suitable notion of (spatial) locality. (biomedcentral.com)
Optionally, the approximation of the joint probability distribution for continuous uncertain parameters may be enhanced using response surface models, which reduces the number of required scenarios and decreases computational demands. (confex.com)
A novel Eulerian particle model tailored for the application in computational fluid dynamics (CFD) is presented. (openu.ac.il)

The present work discusses a novel stochastic reactor model (SRM) based modeling framework capable of predicting the combustion process and the emission formation in a heavy-duty engine running under RCCI combustion mode. (sae.org)
Modeling of Reactivity Controlled Compression Ignition Combustion Using a Stochastic Reactor Model Coupled with Detailed Chemistry," SAE Technical Paper 2021-24-0014, 2021, https://doi.org/10.4271/2021-24-0014 . (sae.org)
Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models.This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. (logesoft.com)
In this work, we use a stochastic reactor model (SRM) closed cycle engine simulation to predict reformate composition accounting for in-cylinder temperature and mixture stratification. (sae.org)
Investigation of Species from Negative Valve Overlap Reforming Using a Stochastic Reactor Model," SAE Technical Paper 2017-01-0529, 2017, https://doi.org/10.4271/2017-01-0529 . (sae.org)

2019 ) A Stochastic SPICE Model for Superconducting Nanowire Single Photon Detectors and Other Nanowire Devices. (academictree.org)

MomentClosure.jl is a tool to automatically obtain time-evolution equations of moments up to an arbitrary order for virtually any chemical reaction network or system of stochastic differential equations (SDEs), implementing a wide array of moment closure approximations commonly used in stochastic biochemical kinetics [1] . (juliapackages.com)
He began his career at Lawrence Berkeley National Laboratory and the Stanford Center for Turbulence Research, where he worked on applying model reduction methods to hyperbolic systems and in developing techniques for locating and tracking singularities of partial differential equations. (pnnl.gov)
Many canonical modelling frameworks, from statistical Bayesian networks to differential equations, have been applied to capture a wide-variety of biological behaviours. (biomedcentral.com)
The lecture develops how to set up reaction schemes for (bio-)chemical reactions, and how to describe them by systems of ordinary differential equations. (tum.de)

A chemical kinetic mechanism composed of 248 species and 1428 reactions was used to describe the oxidation of gasoline and diesel using a primary reference fuel (PRF) mixture and n-heptane, respectively. (sae.org)
This model has the potential to address the different sources of variability that are relevant to transcriptional and translational processes at the molecular level, namely, intrinsic noise due to the stochastic nature of the birth and deaths processes involved in chemical reactions, and extrinsic noise arising from the cell-to-cell variation of kinetic parameters associated with these processes. (warwick.ac.uk)
Certain types of chemical reactions, such as the global deprotection of a polypeptide, are extremely complex. (mst.edu)
As a result, it may be very difficult or expensive to develop accurate models of these chemical reactions. (mst.edu)
Chemical reaction networks containing any number of molecular species and reactions with any type of smooth propensity functions are supported. (juliapackages.com)
Next, researchers use sensitivity analysis to identify the most important reactions responsible for the performance of the skeletal model. (sjsu.edu)
Finally, they perform reaction rate parameter modification for such reactions in order to improve the agreement of detailed and reduced model predictions with literature experimental ignition data. (sjsu.edu)
In this article we focus on the parameter inference problem for stochastic kinetic models of biochemical reactions given discrete time-course observations of either some or all of the molecular species. (biomedcentral.com)
In this talk, a new modeling approach to evaluate the effect of hydrologic fluctuations on soil water chemistry and weathering reactions is analyzed by means of a dynamical system approach. (criticalzone.org)
Some fundamental thermodynamic aspects of the chemical reactions are also discussed. (criticalzone.org)
The model is based on a bivariate moment method and features a full coupling with the gas-phase by kinetic formulations for inception, and activated and non-activated surface reactions. (openu.ac.il)
Due to the absence of crucial activated and non-activated surface reactions, the latter model predicts values that deviate more than one order of magnitude from the experimental data, while the new model shows an overall good agreement. (openu.ac.il)
The course covers theoretical models for the structure and reactions of atomic nuclear, as well as experiments in nuclear physics and their scientific applications. (lu.se)

2018 ) A kinetic-inductance-based superconducting memory element with shunting and sub-nanosecond write times. (academictree.org)

abstract = "A framework for the analysis of stochastic models of chemical systems for which the deterministic mean-field description is undergoing a saddle-node infinite period (SNIPER) bifurcation is presented. (edu.sa)
Abstract: Reaction network models are often used to investigate the dynamics of different species from various branches of chemistry, biology and ecology. (wisc.edu)

Kinetic Theory. (unict.it)
A relative new mesoscopic point of view at that time which is "kinetic theory" was highlighted by Hilbert as the bridge to link the two. (wisc.edu)
In this talk, I will talk about the history and basic elements of kinetic theory and Boltzmann equation, and the role boundary plays for such a system, as well as briefly mention some recent progress. (wisc.edu)

0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. (logesoft.com)
Multiscale Modeling and Simulation , 19(1), pp. 208-241. (pnnl.gov)
On the other hand, the need for stochastic simulation and the typically large dimension of the parameter space hampers the determination of the rate determining steps by sensitivity analysis, i.e. the most interesting input for a rational catalyst design. (fu-berlin.de)
Finite difference approximations for gradient based local sensitivity analysis suffer from the statistical noise in the stochastic simulation results, but also from the typically large number of parameters. (fu-berlin.de)
Error propagation in first-principles kinetic Monte Carlo simulation. (fu-berlin.de)
A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis. (fu-berlin.de)
Moreover, the greatest challenge of the random direction model is the requirement that a border behavior model be specified for the reaction of mobile stations reaching the simulation area boundary. (mecs-press.org)
Interfaces with standard chemical engineering process simulation software (e.g. (confex.com)
It is characterized by high precursor concentrations at moderate heating temperature of 853 K. Further, a new experiment was conducted for the comparison with the new model approach in a three-dimensional, transient simulation. (openu.ac.il)

2021. "A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure. (pnnl.gov)
In order to enable this detailed undestanding, first-principles kinetic Monte Carlo approaches have been established during the last decade. (fu-berlin.de)
Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model. (fu-berlin.de)
Since stochastic models such as chemical master equations are typically solved using a Monte Carlo approach in which only a finite number of Monte Carlo realizations are computationally practical, specific considerations are given to account for the effect of finite sampling in the histogram binning of the state density functions. (biomedcentral.com)
In which cases does it make sense to use Monte Carlo simulations to solve a kinetic system? (tum.de)

[1] D. Schnoerr, G. Sanguinetti, and R. Grima, "Approximation and inference methods for stochastic biochemical kinetics - a tutorial review", Journal of Physics A: Mathematical and Theoretical 50, 093001 (2017). (juliapackages.com)
C. H. Lee, "A Moment Closure Method for Stochastic Chemical Reaction Networks with General Kinetics", MATCH Communications in Mathematical and in Computer Chemistry 70, 785-800 (2013). (juliapackages.com)
D. Schnoerr, G. Sanguinetti, and R. Grima, "Comparison of different moment-closure approximations for stochastic chemical kinetics", The Journal of Chemical Physics 143, 185101 (2015). (juliapackages.com)
This work contributes toward improved understanding and modeling of the oxidation kinetics of conventional and bio-derived transportation biofuels, as well as the estimation of laminar burning velocity that can be encountered in turbulent combustion simulations. (sjsu.edu)

The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equation. (biomedcentral.com)
Although the subject of parameter estimation is well-established for deterministic models, it is not yet routine for the chemical master equation. (biomedcentral.com)
Thus, the purpose of this work is to develop practical and effective methods for estimating kinetic model parameters in the chemical master equation and other stochastic models from single cell and cell population experimental data. (biomedcentral.com)

Furthermore, we utilize flux balance analysis and show how to automatically construct reversible jump samplers for arbitrary biochemical reaction models. (biomedcentral.com)

The proposed modeling approach represents a promising basis towards establishing a comprehensive modeling framework capable of simulating transient operation as well as fuel property sweeps with acceptable accuracy. (sae.org)
Several of these models make use of a continuum approach where platelets, platelet agonists, and coagulation factors are treated as chemical species that obey the convection-diffusion-reaction equation for species transport [ 11 - 15 ]. (frontiersin.org)
The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry. (logesoft.com)
The advantage of the probability density function approach compared to mean value models is its capability to account for temperature and mixture inhomogeneities. (logesoft.com)
Our approach is based on the chemical Fokker-Planck equation. (edu.sa)
The study implements a Stochastic Species Elimination (SSE) reduction approach to develop multiple skeletal versions of a detailed chemical kinetic model of THF from the literature based on ignition delay time simulations at various pressures and temperatures. (sjsu.edu)
The parameter estimation methodologies described in this work have provided an effective and practical approach in the estimation of kinetic parameters of stochastic systems from either sparse or dense cell population data. (biomedcentral.com)
A promising approach is represented by the study of biological phenomena as a collection of interactive entities through process calculi equipped with stochastic semantics. (biomedcentral.com)
The compositionality of the approach has permitted us to independently focus on tuning the models of the pre- and post- synaptic traits, and then to naturally connect them, by dealing with "interface" issues. (biomedcentral.com)
Taking advantage of the compositionality of the approach, an enhanced model could then be composed with other neural models, designed within the same framework, in order to obtain a more detailed and comprehensive model. (biomedcentral.com)
Kinetic Approach to Elasticity Analysis of D2D Links Quality Indicators Under Non-stationary Random Walk Mobility Model. (mecs-press.org)
A popular approach for process design under uncertainty involves formulation of a two-stage stochastic (e.g., bi-level optimization) problem, where design variables (e.g., flowsheet topology, size and number of units, etc.) are determined in the first step and operating variables (e.g., flowrates, stream pressures, etc.) are determined in the second step, after the uncertain parameters are realized. (confex.com)
Pauline's research focuses on building such models through a physics-informed learning based approach, taking advantage of the available measurements. (lu.se)

The ACM model consists of approximately 150,000 equations which result from discretization of partial differential algebraic equation adsorber and regenerator bed models. (confex.com)

A. Ale, P. Kirk, and M. P. H. Stumpf, "A general moment expansion method for stochastic kinetic models", The Journal of Chemical Physics 138, 174101 (2013). (juliapackages.com)
E. Lakatos, A. Ale, P. D. W. Kirk, and M. P. H. Stumpf, "Multivariate moment closure techniques for stochastic kinetic models", The Journal of Chemical Physics 143, 094107 (2015). (juliapackages.com)
The Journal of Chemical Physics 157, no. 14:Art. (pnnl.gov)

2021. "Time-dependent stochastic basis adaptation for uncertainty quantification. (pnnl.gov)

2020. "Improving time-step convergence in an atmosphere model with simplified physics: using mathematical rigor to avoid nonphysical behavior in a parameterization. (pnnl.gov)
Deterministic strategies are generally only applicable for specific mathematical formulations of the model where a statement about the existence of the global optimum can be guaranteed along with a constructive algorithm to find it. (biomedcentral.com)
Mathematical models form a cornerstone of systems biology and these models are usually constructed from available biological knowledge and data, which once validated, are subsequently analyzed to address specific biological questions. (biomedcentral.com)
During the last decades, the development of high-throughput technologies has produced a huge amount of information in the field of neurobiology, requiring the utilization of mathematical modeling to describe the complex dynamics of biological processes and stimulating new collaborations among biologists, physicists and computer scientists [ 1 , 2 ]. (biomedcentral.com)
Various types of mathematical models and systems analyses of biological networks have further been used to gain a better understanding of the sources and regulatory mechanisms of such variability. (mdpi.com)
We have proposed the mathematical model to molar un-conservative reactive distillation system are developed a general geometric shortcut design method by formulating the boundary value method into an optimization problem. (ncl.edu.tw)
He is a full professor at the Technical University of Munich, holding the chair 'Mathematical Modelling of Biological Systems', associate faculty at the Wellcome Trust Sanger Institute as well as adjunct faculty at the Northwestern University. (lu.se)

The SGD method proposed in the paper presents a general framework of inferring parameters for stochastic kinetic models. (biomedcentral.com)

The dependence of the mean period of these oscillations on the parameters of the model (kinetic rate constants) and the size of the system (number of molecules present) are studied. (edu.sa)
As in other modelling frameworks, the accompanying rate constants are important for the end-applications like analyzing system properties (e.g. robustness) or predicting the effects of genetic perturbations. (biomedcentral.com)

The study uses ignition delay time simulations using detailed and skeletal models, with good agreement observed at higher temperatures. (sjsu.edu)
Further, solutions based on 'classical', approximation procedures, computer-based numerical calculations, and stochastic simulations are presented and discussed. (tum.de)
The SRM model is less computationally intensive than CFD simulations while still allowing the use of large chemical mechanisms to predict intermediate species formation rates. (sae.org)

To overcome this limitation, we developed a fully three-dimensional multiscale model for platelet aggregation under flow and validated model predictions against experimental observations in prior work [ 9 ]. (frontiersin.org)

Our model can be generalized to describe a variety of phenomena in nano-photonics and plasmonic systems. (urosario.edu.co)
These allow both the phenomena investigated to be precisely modeled and virtual experiments to be performed in silico . (biomedcentral.com)
Drawing from recent advances in the dynamics and control of distributed parameter processes for which continuum laws are applicable as well as stochastic modeling of phenomena at mesoscopic/microscopic length scales, control and optimization of multiscale process systems has evolved into a very active research area of systems and control engineering. (umd.edu)

The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available. (sae.org)
The goal is to use the obtained models to control power consumption and to build predictive models for production planning. (lu.se)

Stochastic optimization is applied in this work to an example process step to obtain the optimum reaction temperature and reaction time. (mst.edu)
Optimization under uncertainty (OUU) allows for uncertain parameters in the process model to be systematically accounted for during optimization, which reduces the risk of poor performance far from the expected values (e.g., average) of the uncertain parameters. (confex.com)
Traditionally, stochastic programs for process design (or planning/scheduling) are typically solved in algebraic modeling environments such as GAMS or AMPL, which automatically calculate exact derivations and interface with powerful, large-scale optimization algorithms. (confex.com)
This paper focuses on computationally tractable formulations for process optimization under uncertainty with rigorous models and process simulators. (confex.com)
The capture system model and the inner optimization problem are solved in ACM. (confex.com)

A key result is that it is possible to define an apparent equilibrium constant that regulates the competition of the photonic processes that take place, an idea conceptually similar to Einstein's model for spontaneous emission and how it can be connected to induced emission in atoms and molecules but including an extension to nonlinear optical and relaxation processes. (urosario.edu.co)
In this model, equilibrium is assumed for the aqueous carbonate system while a kinetic law is adopted for the weathering reaction. (criticalzone.org)
In my research I connect models of nuclear , hadronic and particle physics with methods of relativistic hydrodynamics, statistical physics and out-of-equilibrium dynamics to study the hot and dense nuclear matter created in high-energy hadron collisions. (aleksas.eu)
Adsorption Coefficient (Koc)-- The ratio of the amount of a chemical adsorbed per unit surface area or per unit weight of organic carbon of a specific particle size in the soil or sediment to the concentration of the chemical in solution at equilibrium. (cdc.gov)

The combination of physical turbulence models, detailed emission formation sub-models and state-of-the-art chemical kinetic mechanisms enables the model to be computationally inexpensive compared to the 3D-CFD approaches. (sae.org)

By comparing model results with experimental speciation data from a single-cylinder engine, the presented work provides insight into the thermodynamic and kinetic processes that occur during in-cylinder fuel reformation. (sae.org)

We show that in this case, the nonlinear optics processes (absorption and scattering) along the optical path can be described using an analogy with the kinetic processes that occur in a chemical reaction. (urosario.edu.co)
By introducing a stochastic rainfall forcing, we then analyze the system probabilistically, and through averaging techniques determine the inter-annual response of the nonlinear stochastic system to the climatic regime and hydrologic parameters (e.g. (criticalzone.org)

We propose an algorithm for inference of kinetic rate parameters based upon maximum likelihood using stochastic gradient descent (SGD). (biomedcentral.com)

Association between microstructure of ingestive behavior and body weight loss in patients one year after Roux-en-Y gastric bypass. (kfki.hu)
Researchers address the second challenge in a chemical kinetic modeling study of the high-temperature ignition behavior of Tetrahydrofuran (THF), a promising second-generation transportation biofuel. (sjsu.edu)
Pauline Kergus uses artificial intelligence to model the thermal behavior of buildings. (lu.se)
In order to explore this feature, it is important to model building's thermal behavior in order to enable the use of demand-side management control strategies. (lu.se)

We present a two-dimensional continuous-time Bayesian hierarchical model based on van Kampen's linear noise approximation. (warwick.ac.uk)

Therefore, a turbulence model is proposed to calculate the mixing time depending on turbulent kinetic energy and its dissipation. (logesoft.com)
The turbulence model accounts for density, swirl, squish and injection effects on turbulent kinetic energy within the combustion chamber. (logesoft.com)

8]Jogendra K., & Panda M. (2016).Ad hoc network routing protocols on random waypoint model. (mecs-press.org)
Calabrese, S., A. Parolari, A.M. Porporato (2016): The dynamical system of weathering: deterministic and stochastic analysis. (criticalzone.org)

Researchers examine parametric dependence of flame time and ignition delay time on pressure, temperature and equivalence ratio for methane, based on validated chemical kinetic mechanisms. (sjsu.edu)
Sensitivity analysis over several parameters of the model has provided results that may help clarify the dynamics of synaptic transmission, while experiments with the model of the complete synapse seem worth explaining short-term plasticity mechanisms. (biomedcentral.com)
In the long term, we are interested, in particular, in addressing models of synaptic plasticity, i.e. activity dependent mechanisms, which are the bases of memory and learning processes. (biomedcentral.com)

Furthermore, in dynamical models, the time resolution of data is naturally of great importance. (biomedcentral.com)
I will first introduce the basic dynamical models for reaction network: the deterministic and stochastic models. (wisc.edu)

The availability of multiple single cell data provides a unique opportunity to estimate such a model and explicitly quantify the sources of variation from experimental data. (warwick.ac.uk)
As a first test, an existing 2-butanone model was examined against the experimental data with the main aim to identify elements of the model that may need improvement. (logesoft.com)
Prior knowledge of kinetic constants is usually limited and the model identification routine typically includes parameter estimation from experimental data. (biomedcentral.com)
However, unlike differential equation models, the identification of stochastic models from experimental data of single cell or cell population data are not yet routine. (biomedcentral.com)

We have developed such a stochastic model starting from existing kinetic models based on ODEs of some sub-components of the synapse, integrating other data from literature and making some assumptions about non-fully understood processes. (biomedcentral.com)

Today numerical models are a major part of the diesel engine development. (logesoft.com)

The aims of the sessions are: i) to introduce students to the tools available for modeling chemical reaction networks, ii) to provide insight into how to build reaction network models for certain types of behaviour, iii) to explore methods for finding behaviour, and iv) to give experience in parameter estimation and kinetic data fitting. (europa.eu)
Nevertheless, similar to kinetic parameter estimation in other modelling frameworks, not all parameters can be estimated accurately, which is a common problem arising from the lack of complete parameter identifiability from the available data. (biomedcentral.com)

Panos Stinis specializes in scientific computing with application interests in model reduction of complex systems, multiscale modeling, uncertainty quantification, and machine learning. (pnnl.gov)

We construct a kinetic model, analogous to a simple chemical reaction, to describe the spatial propagation of the electromagnetic fields in four-wave mixing spectroscopy in a two-level molecular model, explicitly taking into account the stochastic effects of the solvent. (urosario.edu.co)
In these examples, the distribution of cells is simulated by stochastic models that describe the probability density function (PDF) of cellular states. (biomedcentral.com)

Pseudo-marginal Metropolis-Hastings: This method replaces the evaluation of the density of the target distribution with an unbiased estimate and is useful when the target density is not available analytically, e.g. latent variable models. (wikipedia.org)
In contrast to soluble chemicals, cadmium oxide particles on a cm2/ml media basis, but are only ~50 particles can settle, diffuse, and aggregate differentially accord- times more potent when differences in delivery to adherent cells are ing to their size, density, and surface physicochemistry. (cdc.gov)

This model falls under the class of hybrid multiscale models where blood velocity and platelet agonists are treated as continuum fields while platelets are resolved explicitly [ 2 - 10 ]. (frontiersin.org)

The Ising model for ferromagnetism and model of the lattice gas. (unict.it)

In Bayesian statistics, the recent development of MCMC methods has made it possible to compute large hierarchical models that require integrations over hundreds to thousands of unknown parameters. (wikipedia.org)

Our methods are illustrated with two examples: a birth-death model and an auto-regulatory gene network. (biomedcentral.com)
The strategies of these methods can be classified as either deterministic or stochastic. (biomedcentral.com)
Our manuscript titled "DNA base order parameter determination without influence of chemical exchange" has been accepted for publication in Methods . (utmb.edu)
A comparison with the results of stochastic methods serves as further benchmark for the presented model. (openu.ac.il)

The relationship between thermal stratification and resulting reformed species provides insight into the effect of non-homogeneity on products and illustrates the value of SRM over homogeneous reactor models to inexpensively predict in-cylinder processes. (sae.org)

It is shown that the stochastic system possesses oscillatory solutions even for parameter values for which the mean-field model does not oscillate. (edu.sa)

Experiments have confirmed the coherence of our model with known biological data, also validating the assumptions made. (biomedcentral.com)

Across thermal stratification levels, the modeled reformate concentrations match well with measured values though they are very sensitive to initial conditions. (sae.org)
We illustrate screening of hazards posed by new products and environmental that where equal mass concentrations (mg/ml) imply equal doses for chemicals (Bakand et al. (cdc.gov)

The variability of kinetic parameters describing human performance of manual material handling activities was investigated, as well as the effects of different variables on the magnitude of this variability. (cdc.gov)
Examination of the trunk motion data using the biomechanical model indicated a significant effect due to the load weight with greater weight levels having higher levels of variability. (cdc.gov)

2020. "Improving solution accuracy and convergence for stochastic physics parameterizations with colored noise. (pnnl.gov)
2020. "Improving timestep convergence in an atmosphere model with simplified physics: the impacts of closure assumption and process coupling. (pnnl.gov)
Vincent Omollo Nyangaresi, Silvance O. Abeka, Anthony J. Rodrigues, "Tracking Area Boundary-aware Protocol for Pseudo Stochastic Mobility Prediction in LTE Networks", International Journal of Information Technology and Computer Science(IJITCS), Vol.12, No.5, pp.52-62, 2020. (mecs-press.org)

On the route to a more efficient exploitation of energy and materials, the design of new heterogenous catalysts is a central aspect, be it for the production of fine chemicals or the conversion of solar energy to fuels. (fu-berlin.de)
Three single-component fuels (iso-octane, n-heptane and ethanol) were modeled as a function of assumed thermal stratification. (sae.org)

Analytical, Diagnostic and Therapeutic Techniques and Equipment3

Phenomena and Processes2

Health Care1

Computational12

Reactor model5

20191

Differential equations4

Reactions13

20181

Abstract2

Theory3

Simulation9

Monte Carlo5

Kinetics4

Master equation3

Biochemical1

Approach13

Equations1

Journal of Chem3

20211

Mathematical7

Framework1

Rate constants2

Simulations3

Multiscale model1

Phenomena3

Predictive2

Optimization5

Equilibrium4

Computationally1

Thermodynamic1

Nonlinear2

Inference1

Behavior4

Approximation1

Turbulence2

20162

Mechanisms3

Dynamical models2

Experimental data4

ODEs1

Numerical1

Estimation2

Uncertainty1

Describe2

Density2

Explicitly1

Lattice1

Bayesian1

Methods4

Species1

System1

Biological1

Concentrations2

Variability2

20203

Fuels2